This invention relates to a method and system for processing medical image data to aid in the detection and diagnosis of disease, and more particularly, to a method and system for detecting lung disease in medical images obtained from a x-ray computed tomography (CT) system.
A x-ray chest radiograph system is the more commonly used diagnostic tool useful for the purpose of detecting lung disease in humans. Lung disease such as bronchitis, emphesema and lung cancer are also detectable in chest radiographs and CT. However, CT systems generally provide over 80 separate images for a single CT scan thereby providing a considerable amount of information to a radiologist for use in interpreting the images and detecting suspect regions that may indicate disease.
Suspect regions are defined as those regions a trained radiologist would recommend following through subsequent diagnostic imaging, biopsy, functional lung testing, or other methods. The considerable volume of data presented by a single CT scan presents a time-consuming process for radiologists. Conventional lung cancer screening generally involves a manual interpretation of the 80 or more images by the radiologist. Fatigue is therefore a significant factor affecting sensitivity and specificity of the human reading. In other diseases, such as emphysema, it is difficult for a radiologist to classify the extent of disease progression by only looking at the CT images.
Chronic Obstructive Pulmonary Disease (COPD) is identified based on symptoms including coughing, wheezing, and shortness of breath (dyspnea). COPD includes a number of respiratory diseases, the most prominent of which are emphysema and chronic bronchitis. COPD affects large airways, small airways and parenchyma in patients. Diseases are typically caused by smoking and air pollution, and are linked to genetic predisposition causing alpha-anti-elastase deficiency.
Emphysema, or airspace destruction, is the most prominent feature of parenchymal change in COPD patients. Emphysema is the result of the loss of elastic recoil of lung tissue. There are four types of emphysema: centrilobular, panlobular or panacinar, distal acinar or paraseptal, and irregular. The first two types contribute to the majority of emphysematous COPD. The classification is based on the anatomical distribution of airspace destruction within a lobule, which is a cluster of acini. Currently, emphysema can be classified only through post mortem examination. Emphysema is typically diagnosed by gross physiological responses, medical imaging and post mortem anatomical inspection.
Chronic bronchitis causes anatomical airway narrowing, which reduces lung function. Airway modification typically begins with irritation from smoking and/or air pollution and can be caused/exacerbated by biological infection. Chronic bronchitis is clinically defined by persistent cough and sputum production for more than 3 months in a 2-year period. Chronic bronchitis can be classified into simple chronic bronchitis, obstructive bronchitis and chronic asthmatic bronchitis. In simple chronic bronchitis, no sputum is produced. Chronic asthmatic bronchitis involves hyperreactivity of the airways. In obstructive chronic bronchitis, airflow is hindered by airway modification. Chronic bronchitis is currently staged using Reid index post mortem. High resolution CT may enable scoring chronic bronchitis using Reid index in vivo.
Bronchial wall cross-sectional area is a key indicator in the diagnosis and staging of COPD. Measuring airway cross-sectional area from medical images (for instance CT) will enable physicians to track disease progression and accelerate clinical trials. Bronchial passages appear in CT images as small dark regions surrounded by bright regions. The dark area is the lumen while the bright area is composed of both the bronchial wall and any attaching or adjacent blood vessels. In measuring the airway wall cross-sectional area, one must not incorporate the thickness of the attaching or adjacent blood vessels.
If the airway is isolated, with no attaching or adjacent blood vessels, the airway can be measured using a variety of standard image processing and computer vision techniques. When the imaged airway has attached of adjacent blood vessels, an example of traditional approach has been to manually select a ray from the center of the lumen that passes through the airway wall at a point where the are no blood vessels. The measure of the wall thickness along this single ray is used to estimate the airway cross-sectional area.
What is needed is a robust method and system for measuring airways to enable diagnosis and tracking of various diseases of COPD.